Datasets
GUE human core-promoter data; the paper evaluates a broader collection of human and mouse classification datasets.
Task
human core-promoter classification
Human core-promoter classification is evaluated as a constituent task of the GUE sequence-classification benchmark.
Sources
EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captionsOverview
Metrics
Matthews correlation coefficient is the primary benchmark metric.
Allowed inputs
DNA sequences.
Sources
EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captionsEvaluation procedure diagram
How it worksComputational evaluation flow
Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol.
Sources
EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captionslimited source coverage · Automated source review, 2026-09-16. All specifications and missing details
Results
Results are available, but no reviewed comparison panel is linked in this release.
All evaluations
1 evaluation · 1 result. Different protocols are not a single leaderboard.
Filter evaluations
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: DNABERT-2 | Task: human core-promoter classification Dataset: GUE H-CPD | 70.5% MCC percent · unknown Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceDNABERT-2: human core-promoter classification DNABERT-2 comparator in consolidated H-CPD table; rerun provenance not explicit Aggregation: Not reported EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Table 5, DNABERT-2 row, H-CPD (MCC) column |
Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.
Methods and evaluation design
Procedure, tasks and evaluated configurations
How it works
Evaluation methodology
GUE human core-promoter data; the paper evaluates a broader collection of human and mouse classification datasets. Predefined training, validation and test subsets supplied with GUE. Matthews correlation coefficient is the primary benchmark metric. OneHot with the high-frequency branch and K-merFreq with XGBoost are controlled in-house baselines; other methods include literature-reported results. Mean and standard deviation across five independent evaluations are reported for EDEN and the OneHot/HFBranch baseline; imported results keep their original reporting conventions.
Sources
EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captionsRecorded evaluations
Each evaluation records what was tested and under which conditions.
Run instructions
No runnable recipe has been reviewed for this task. Dataset access, model requirements, licences and compute requirements must be checked against its sources before execution.
A task describes a biological question. Choose a linked protocol to obtain concrete split and scoring instructions.
Strengths, limitations and unresolved questions
Strengths and limitations
Strengths and considerations
No source-reviewed explanatory claims are recorded here yet.
Limitations and conditions
- Task-level scores are tied to the reused dataset partitions. Predefined partitions alone do not establish absence of genomic or pretraining overlap.
Sources
EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions
Profile review details
Relevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged.
Stable record: reported-task-9f62e739c6371eSpecifications
Inputs, training, access and other details
Explanatory profile: limited source coverage · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.
| Property | Description and evidence |
|---|---|
| Datasets | GUE human core-promoter data; the paper evaluates a broader collection of human and mouse classification datasets.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
| Splits | Predefined training, validation and test subsets supplied with GUE.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
| Metrics | Matthews correlation coefficient is the primary benchmark metric.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
| Baselines | OneHot with the high-frequency branch and K-merFreq with XGBoost are controlled in-house baselines; other methods include literature-reported results.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
| Leakage controls | The evaluation uses predefined training, validation and test subsets of the reused genomic datasets. The inspected dataset and implementation sections do not document an additional chromosome-, locus- or sequence-similarity exclusion audit, or an audit of foundation-model pretraining overlap. · Not reported in inspected sourcesSourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Experimental settings: datasets and implementation; cached paragraphs 116–137 |
| Uncertainty | Mean and standard deviation across five independent evaluations are reported for EDEN and the OneHot/HFBranch baseline; imported results keep their original reporting conventions.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
| Entity type | Paper-specific computational evaluation protocol.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
| Organisms | Human for the core-promoter task; the broader suite also contains mouse datasets.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
| Assays | GUE promoter/non-promoter annotations.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
| Allowed inputs | DNA sequences.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
| Adaptation | Supervised classification using the predefined GUE train/validation/test data.SourcesEDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions |
Evidence
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
Papers and result coverage
Last literature check: 2026-09-17. Dated primary-source discovery and protocol/table screening. Source checking does not mean experimental reproduction. Only separately extracted and independently reviewed numeric batches are publishable.
| Paper or primary resource | Version | Reference |
|---|---|---|
| EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning | journal full text in PMC | Read source |
Historical gaps recorded on 2026-09-17
The catalogue now holds 1 result rows for this benchmark. A note below about pending extraction describes the state on 2026-09-17 and may since have been answered by a later batch. The result rows and their sources are the current record.
- complete numerical transcription and independent cell review: Full primary artifact and table inventory preserved; no new numeric row is published from this audit alone.
- exact checkpoint hashes and per-method scored denominators: Table labels alone do not establish these fields; do not infer checkpoint or scored count from model name or dataset size.
Search and extraction details
primary comparison tables located
Searches
- EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning 10.1186/s12859-026-06367-6
Evidence locations
- Table 5; XML table Tab5
Evidence table
Inspect claims, sources and review details
Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.
One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
17 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Diagram caption Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol. Individual claims | EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions Version: journal full text in PMC | source checked automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Diagram steps
| EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions Version: journal full text in PMC | source checked automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Computational evaluation flow Individual claims | EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions Version: journal full text in PMC | source checked automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Datasets GUE human core-promoter data; the paper evaluates a broader collection of human and mouse classification datasets. Individual claims | EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions Version: journal full text in PMC | source checked automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Splits Predefined training, validation and test subsets supplied with GUE. Individual claims | EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions Version: journal full text in PMC | source checked automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Adaptation Supervised classification using the predefined GUE train/validation/test data. Individual claims | EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions Version: journal full text in PMC | source checked automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Metrics Matthews correlation coefficient is the primary benchmark metric. Individual claims | EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions Version: journal full text in PMC | source checked automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Baselines OneHot with the high-frequency branch and K-merFreq with XGBoost are controlled in-house baselines; other methods include literature-reported results. Individual claims | EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions Version: journal full text in PMC | source checked automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Leakage controls The evaluation uses predefined training, validation and test subsets of the reused genomic datasets. The inspected dataset and implementation sections do not document an additional chromosome-, locus- or sequence-similarity exclusion audit, or an audit of foundation-model pretraining overlap. Individual claims | EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Experimental settings: datasets and implementation; cached paragraphs 116–137 Version: journal full text in PMC | unreported automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Uncertainty Mean and standard deviation across five independent evaluations are reported for EDEN and the OneHot/HFBranch baseline; imported results keep their original reporting conventions. Individual claims | EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions Version: journal full text in PMC | source checked automated source review · 2026-09-16 Audit detailsRelevant full-paper computational evaluation sections, tables/captions and cited supplementary task passages were reviewed. Reporting omissions are scoped to the inspected sources. Original numerical results are unchanged. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
View linked audit checks and correction history
Release 2026-09-29-06401fd5b220 · Record review: needs review
2 source records and release history
- EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Original source · journal full text in PMC
- EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning · Original source · journal full text in PMC
Technical metadata and extraction receipts
Stable ID: reported-task-9f62e739c6371e
- areas
- dna-genomes
- tasks
- human core-promoter classification
- entity level
- task
- version
- Not reported
- task
- human core-promoter classification
- scope note
- Paper-specific evaluation task; protocol completeness requires further extraction.
- benchmark research
- review date: 2026-09-17; status: primary_comparison_tables_located; primary sources: evidence-expansion-eden-genomic-classification-2026-38a6e26b; inspected locators: Table 5; XML table Tab5; searched queries: EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning 10.1186/s12859-026-06367-6; gaps: complete numerical transcription and independent cell review: Full primary artifact and table inventory preserved; no new numeric row is published from this audit alone.; exact checkpoint hashes and per-method scored denominators: Table labels alone do not establish these fields; do not infer checkpoint or scored count from model name or dataset size.; claim scope: Dated primary-source discovery and protocol/table screening. Source checking does not mean experimental reproduction. Only separately extracted and independently reviewed numeric batches are publishable.
- historical missing metadata
- protocol version: not_reported_in_legacy_extract
- metadata review scope
- historical_missing_metadata preserves the original discovery state. Current descriptive evidence and missingness are recorded in profile.facts; numerical-result review is separate.
- legacy kinds
- benchmark
- entity classification
- review date: 2026-09-17; rationale: This source-scoped record identifies the biological prediction task and holds its paper context. Preserve the existing task identity; exact split, model adaptation and scoring remain in linked evaluations or separate protocol records.; source ids: eden-genomic-classification-2026; source locator: Methods: Datasets; cached text lines 119–120; uncertainty/repeat-run/statistical-comparison passages; matching task comparison table/ablation captions; ambiguities: A paper- or suite-specific task may constrain some inputs or metrics; that alone does not make it interchangeable with a complete versioned protocol. No protocol equivalence is inferred.; Some legacy profile Entity type facts use the generic phrase computational evaluation protocol. That boilerplate is not sufficient to establish a single fixed protocol identity or to merge this task with another protocol record.
Related records
- dataset: GUE H-CPD
- benchmark: DNABERT-2: human core-promoter classification